Sensitivity calibration of a three-axis accelerometer under different temperature conditions using the hybrid GA–PSO–BPNN algorithm

Sensor Review ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Cuicui Du ◽  
Deren Kong
Keyword(s):  
Hybrid Genetic Algorithm ◽  
Global Search ◽  
Convergence Speed ◽  
Fast Convergence ◽  
Calibration Error ◽  
Content Type ◽  
Linear Fitting ◽  
Temperature Conditions ◽  
Non Linear ◽  
Different Temperatures

Purpose Three-axis accelerometers play a vital role in monitoring the vibrations in aircraft machinery, especially in variable flight temperature environments. The sensitivity of a three-axis accelerometer under different temperature conditions needs to be calibrated before the flight test. Hence, the authors investigated the efficiency and sensitivity calibration of three-axis accelerometers under different conditions. This paper aims to propose the novel calibration algorithm for the three-axis accelerometers or the similar accelerometers. Design/methodology/approach The authors propose a hybrid genetic algorithm–particle swarm optimisation–back-propagation neural network (GA–PSO–BPNN) algorithm. This method has high global search ability, fast convergence speed and strong non-linear fitting capability; it follows the rules of natural selection and survival of the fittest. The authors describe the experimental setup for the calibration of the three-axis accelerometer using a three-comprehensive electrodynamic vibration test box, which provides different temperatures. Furthermore, to evaluate the performance of the hybrid GA–PSO–BPNN algorithm for sensitivity calibration, the authors performed a detailed comparative experimental analysis of the BPNN, GA–BPNN, PSO–BPNN and GA–PSO–BPNN algorithms under different temperatures (−55, 0 , 25 and 70 °C). Findings It has been showed that the prediction error of three-axis accelerometer under the hybrid GA–PSO–BPNN algorithm is the least (approximately ±0.1), which proved that the proposed GA–PSO–BPNN algorithm performed well on the sensitivity calibration of the three-axis accelerometer under different temperatures conditions. Originality/value The designed GA–PSO–BPNN algorithm with high global search ability, fast convergence speed and strong non-linear fitting capability has been proposed to decrease the sensitivity calibration error of three-axis accelerometer, and the hybrid algorithm could reach the global optimal solution rapidly and accurately.

Experimental and Theoretical (ab initio and DFT) Analysis of UV-Vis Spectra, Thermodynamic Functions and Non-linear Optical Properties of 2-Chloro-3,4-Dimethoxybenzaldehyde

2015 ◽  
Vol 8 (2) ◽  
pp. 2122-2134
Author(s):  
Sarvendra Kumar ◽  
Rajesh Kumar ◽  
Jayant Teotia ◽  
M. K. Yadav
Keyword(s):  
Thermodynamic Functions ◽  
Title Compound ◽  
Density Functional ◽  
Structural Characteristics ◽  
Basis Sets ◽  
Ultraviolet Absorption Spectrum ◽  
Non Linear ◽  
Different Temperatures ◽  
Linear Optical Properties ◽  
Linear Optical

In the present work, UV- Visible spectra of 2-Chloro-3,4-Dimethoxybenzaldehyde (2,3,4-CDMB) compound  have been carried out experimentally and theoretically. The ultraviolet absorption spectrum of title compound in three solvents (Acetone, Diethyl Ether, CCl4) of different polarity were examined in the range of 200–500 nm. The structure of the molecule was optimized and the structural characteristics were determined by HF and DFT (B3LYP) methods with 6-31+G(d,p) and 6-311++G(d,p) as basis sets. The excitation energy, wavelength corresponds to absorption maxima () and oscillator strength (f) are calculated by Time-Dependent Density Functional Theory (TD-DFT) using B3LYP/6-31+G(d,p) and B3LYP/6-311++G(d,p) as basis sets. The electric dipole moment (μ), polarizability (α) and the first hyperpolarizability (β ) have been computed to evaluate the non-linear optical (NLO) response of the investigated compound by HF and DFT (B3LYP) with already mentioned basis sets. Thermodynamic functions of the title compound at different temperatures were also calculated.

A UMDA-Based Discretization Method for Continuous Attributes

2011 ◽  
Vol 403-408 ◽  
pp. 1834-1838
Author(s):  
Jing Zhao ◽  
Chong Zhao Han ◽  
Bin Wei ◽  
De Qiang Han
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Evolutionary Algorithms ◽  
Marginal Distribution ◽  
Convergence Speed ◽  
Fast Convergence ◽  
Experimental Results ◽  
Discretization Method ◽  
Bottom Up ◽  
Global Dynamic

Discretization of continuous attributes have played an important role in machine learning and data mining. They can not only improve the performance of the classifier, but also reduce the space of the storage. Univariate Marginal Distribution Algorithm is a modified Evolutionary Algorithms, which has some advantages over classical Evolutionary Algorithms such as the fast convergence speed and few parameters need to be tuned. In this paper, we proposed a bottom-up, global, dynamic, and supervised discretization method on the basis of Univariate Marginal Distribution Algorithm.The experimental results showed that the proposed method could effectively improve the accuracy of classifier.

scholarly journals Non-linear fitting with joint spatial regularization in Arterial Spin Labeling

2021 ◽  
pp. 102067
Author(s):  
Oliver Maier ◽  
Stefan M. Spann ◽  
Daniela Pinter ◽  
Thomas Gattringer ◽  
Nicole Hinteregger ◽  
...  
Keyword(s):  
Arterial Spin Labeling ◽  
Spin Labeling ◽  
Linear Fitting ◽  
Non Linear ◽  
Spatial Regularization

scholarly journals Kinetic, isotherm and thermodynamic studies with linear and non-linear fitting for cadmium(II) removal by black carbon of pine cone

2017 ◽  
Vol 76 (8) ◽  
pp. 2242-2253 ◽  
Author(s):  
Z. Yavari ◽  
M. Noroozifar
Keyword(s):  
Aqueous Solutions ◽  
Black Carbon ◽  
Adsorption Process ◽  
Order Kinetic ◽  
Cadmium Removal ◽  
Thermodynamic Studies ◽  
Linear Fitting ◽  
Pine Cone ◽  
Fitting Method ◽  
Non Linear

In this study, black carbon from pine cone (BCPC) and acidic-modified BCPC (MBCPC) powder as a popular agricultural waste in the southeast of Iran were used for cadmium removal from aqueous solutions. The effect of various factors, such as surface chemistry and dosage of adsorbent, contact time, size of particles, initial concentration of cadmium, temperature, and pH of aqueous solutions, was investigated. The results show cadmium removal with usage of the mentioned adsorbents increased after acidic modification. It was noteworthy in this work that the removal percentage of pollutant was above 90% for suggested biosorbents. The obtained experimental data for optimum conditions were selected to model the adsorption behavior of the materials with usage of six isotherm equations via non-linear fitting method and the residual root mean square error estimation for each model. The adsorption of cadmium preferably fitted Khan and Langmuir–Freundlich isotherms for BCPC and MBCPC adsorbents, respectively. The kinetic studies via linear fitting method proved the second-order kinetic was the applicable model for the adsorption process. Thermodynamic studies show the adsorption process of cadmium onto BCPC and MBCPC was spontaneous and endothermic.

A batch-wise non-linear fitting and analysis tool for treating large X-ray diffraction data sets

2006 ◽  
Vol 39 (2) ◽  
pp. 262-266 ◽  
Author(s):  
R. J. Davies
Keyword(s):  
Diffraction Data ◽  
Operation Mode ◽  
Large Data ◽  
Scattering Data ◽  
Data Sets ◽  
Analysis Tool ◽  
Data Set ◽  
X Ray ◽  
Linear Fitting ◽  
Non Linear

Synchrotron sources offer high-brilliance X-ray beams which are ideal for spatially and time-resolved studies. Large amounts of wide- and small-angle X-ray scattering data can now be generated rapidly, for example, during routine scanning experiments. Consequently, the analysis of the large data sets produced has become a complex and pressing issue. Even relatively simple analyses become difficult when a single data set can contain many thousands of individual diffraction patterns. This article reports on a new software application for the automated analysis of scattering intensity profiles. It is capable of batch-processing thousands of individual data files without user intervention. Diffraction data can be fitted using a combination of background functions and non-linear peak functions. To compliment the batch-wise operation mode, the software includes several specialist algorithms to ensure that the results obtained are reliable. These include peak-tracking, artefact removal, function elimination and spread-estimate fitting. Furthermore, as well as non-linear fitting, the software can calculate integrated intensities and selected orientation parameters.

Heat and mass transfer effects on MHD non-Newtonian fluids flow through an inclined thermally-stratified porous medium

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gladys Tharapatla ◽  
Pamula Rajakumari ◽  
Ramana G.V. Reddy
Keyword(s):  
Mass Transfer ◽  
Porous Medium ◽  
Velocity Profile ◽  
Heat And Mass Transfer ◽  
Newtonian Fluids ◽  
Transfer Effects ◽  
Content Type ◽  
Non Linear ◽  
Homotopy Analysis ◽  
Flow Through

Purpose This paper aims to analyze heat and mass transfer of magnetohydrodynamic (MHD) non-Newtonian fluids flow past an inclined thermally stratified porous plate using a numerical approach. Design/methodology/approach The flow equations are set up with the non-linear free convective term, thermal radiation, nanofluids and Soret–Dufour effects. Thus, the non-linear partial differential equations of the flow analysis were simplified by using similarity transformation to obtain non-linear coupled equations. The set of simplified equations are solved by using the spectral homotopy analysis method (SHAM) and the spectral relaxation method (SRM). SHAM uses the approach of Chebyshev pseudospectral alongside the homotopy analysis. The SRM uses the concept of Gauss-Seidel techniques to the linear system of equations. Findings Findings revealed that a large value of the non-linear convective parameters for both temperature and concentration increases the velocity profile. A large value of the Williamson term is detected to elevate the velocity plot, whereas the Casson parameter degenerates the velocity profile. The thermal radiation was found to elevate both velocity and temperature as its value increases. The imposed magnetic field was found to slow down the fluid velocity by originating the Lorentz force. Originality/value The novelty of this paper is to explore the heat and mass transfer effects on MHD non-Newtonian fluids flow through an inclined thermally-stratified porous medium. The model is formulated in an inclined plate and embedded in a thermally-stratified porous medium which to the best of the knowledge has not been explored before in literature. Two elegance spectral numerical techniques have been used in solving the modeled equations. Both SRM and SHAM were found to be accurate.

An improved sparrow search algorithm based on levy flight and opposition-based learning

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Danni Chen ◽  
JianDong Zhao ◽  
Peng Huang ◽  
Xiongna Deng ◽  
Tingting Lu
Keyword(s):  
Parameter Optimization ◽  
Optimization Problem ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Convergence Speed ◽  
Support Vector ◽  
Lévy Flight ◽  
Levy Flight ◽  
Content Type ◽  
Opposition Based Learning

Purpose Sparrow search algorithm (SSA) is a novel global optimization method, but it is easy to fall into local optimization, which leads to its poor search accuracy and stability. The purpose of this study is to propose an improved SSA algorithm, called levy flight and opposition-based learning (LOSSA), based on LOSSA strategy. The LOSSA shows better search accuracy, faster convergence speed and stronger stability. Design/methodology/approach To further enhance the optimization performance of the algorithm, The Levy flight operation is introduced into the producers search process of the original SSA to enhance the ability of the algorithm to jump out of the local optimum. The opposition-based learning strategy generates better solutions for SSA, which is beneficial to accelerate the convergence speed of the algorithm. On the one hand, the performance of the LOSSA is evaluated by a set of numerical experiments based on classical benchmark functions. On the other hand, the hyper-parameter optimization problem of the Support Vector Machine (SVM) is also used to test the ability of LOSSA to solve practical problems. Findings First of all, the effectiveness of the two improved methods is verified by Wilcoxon signed rank test. Second, the statistical results of the numerical experiment show the significant improvement of the LOSSA compared with the original algorithm and other natural heuristic algorithms. Finally, the feasibility and effectiveness of the LOSSA in solving the hyper-parameter optimization problem of machine learning algorithms are demonstrated. Originality/value An improved SSA based on LOSSA is proposed in this paper. The experimental results show that the overall performance of the LOSSA is satisfactory. Compared with the SSA and other natural heuristic algorithms, the LOSSA shows better search accuracy, faster convergence speed and stronger stability. Moreover, the LOSSA also showed great optimization performance in the hyper-parameter optimization of the SVM model.

Non-linear fitting-based phasor measurement method for PMU calibrator

2019 ◽  
Vol 106 ◽  
pp. 585-597 ◽  
Author(s):  
Hao Liu ◽  
Sudi Xu ◽  
Tianshu Bi ◽  
Kenneth E. Martin ◽  
Cheng Qian ◽  
...  
Keyword(s):  
Measurement Method ◽  
Linear Fitting ◽  
Phasor Measurement ◽  
Non Linear

Linear and non-linear analysis on two-dimensional steel frame under different temperatures

2019 ◽  
Vol 10 (1) ◽  
pp. 48-55
Author(s):  
Parthasarathi N. ◽  
Satyanarayanan K.S. ◽  
Prakash M. ◽  
Thamilarasu V.
Keyword(s):  
High Temperatures ◽  
Progressive Collapse ◽  
Transient State ◽  
Steel Frame ◽  
Frame Structure ◽  
Two Dimensional ◽  
Content Type ◽  
Frame Building ◽  
Different Temperatures ◽  
Steel Frame Structure

Purpose Progressive collapse because of high temperatures arising from an explosion, vehicle impact or fire is an important issue for structural failure in high-rise buildings. Design/methodology/approach The present study, using ABAQUS software for the analysis, investigated the progressive collapse of a two-dimensional, three-bay, four-storey steel frame structure from high-temperature stresses. Findings After structure reaches the temperature results like displacement, stress axial load and shear force are discussed. Research limitations/implications Different temperatures were applied to the columns at different heights of a structure framed with various materials. Progressive collapse load combinations were also applied as per general service administration guidelines. Originality/value This study covered both steady-state and transient-state conditions of a multistorey-frame building subjected to a rise in temperature in the corner columns and intermediate columns. The columns in the framed structure were subjected to high temperatures at different heights, and the resulting displacements, stresses and axial loads were obtained, analysed and discussed.

Non Linear Fitting Methods for Machine Learning

2017 ◽  
pp. 807-818
Author(s):  
Edgar A. Martínez-García ◽  
Nancy Ávila Rodríguez ◽  
Ricardo Rodríguez-Jorge ◽  
Jolanta Mizera-Pietraszko ◽  
Jaichandar Kulandaidaasan Sheba ◽  
...  
Keyword(s):  
Machine Learning ◽  
Linear Fitting ◽  
Non Linear
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